U.S. patent number 10,587,796 [Application Number 15/900,110] was granted by the patent office on 2020-03-10 for technology for automatically ensuring consistent digital image capture parameters.
This patent grant is currently assigned to STATE FARM MUTUAL AUTOMOBILE INSURANCE COMPANY. The grantee listed for this patent is STATE FARM MUTUAL AUTOMOBILE INSURANCE COMPANY. Invention is credited to Lucas Allen, Jeremy T. Cunningham, Bradley A. Sliz.
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United States Patent |
10,587,796 |
Sliz , et al. |
March 10, 2020 |
Technology for automatically ensuring consistent digital image
capture parameters
Abstract
Systems and methods for analyzing image data to automatically
ensure image capture consistency are described. According to
certain aspects, a server may access aerial and other image data
and identify a set of parameters associated with the capture of the
image data. The server may access a corresponding set of acceptable
image capture parameters, and may compare the set of parameters to
the set of acceptable parameters to determine whether image data is
consistent with the set of acceptable parameters. In some
embodiments, if the image data is not consistent, the server may
generate a notification or instruction to cause an image capture
component to recapture additional image data.
Inventors: |
Sliz; Bradley A. (Normal,
IL), Allen; Lucas (East Peoria, IL), Cunningham; Jeremy
T. (Bloomington, IL) |
Applicant: |
Name |
City |
State |
Country |
Type |
STATE FARM MUTUAL AUTOMOBILE INSURANCE COMPANY |
Bloomington |
IL |
US |
|
|
Assignee: |
STATE FARM MUTUAL AUTOMOBILE
INSURANCE COMPANY (Bloomington, IL)
|
Family
ID: |
69723667 |
Appl.
No.: |
15/900,110 |
Filed: |
February 20, 2018 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
Issue Date |
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62483786 |
Apr 10, 2017 |
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62473014 |
Mar 17, 2017 |
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62468806 |
Mar 8, 2017 |
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62463371 |
Feb 24, 2017 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
H04N
5/23206 (20130101); G06T 7/0002 (20130101); H04N
5/23222 (20130101); G06K 9/6215 (20130101); G06K
9/6202 (20130101) |
Current International
Class: |
G06K
9/62 (20060101); H04N 5/232 (20060101); G06T
7/00 (20170101) |
References Cited
[Referenced By]
U.S. Patent Documents
Primary Examiner: Wang; Carol
Attorney, Agent or Firm: Marshall, Gerstein & Borun
LLP
Parent Case Text
CROSS-REFERENCE TO RELATED APPLICATIONS
This application claims benefit of the filing dates of U.S.
Provisional Patent Application No. 62/463,371 (filed Feb. 24, 2017
and entitled "TECHNOLOGY FOR ANALYZING IMAGE DATA TO AUTOMATICALLY
ASSESS CUSTOMER OPPORTUNITIES"); U.S. Provisional Patent
Application No. 62/468,806 (filed Mar. 8, 2017 and entitled
"TECHNOLOGY FOR AUTOMATICALLY ENSURING CONSISTENT DIGITAL IMAGE
CAPTURE PARAMETERS"); U.S. Provisional Patent Application No.
62/473,014 (filed Mar. 17, 2017 and entitled "TECHNOLOGY FOR
ANALYZING IMAGE DATA TO AUTOMATICALLY PROCESS CUSTOMER RENEWALS");
and U.S. Provisional Patent Application No. 62/483,786 (filed Apr.
10, 2017 and entitled "TECHNOLOGY FOR ANALYZING IMAGE DATA TO
AUTOMATICALLY MANAGE CUSTOMER POLICIES")--which are hereby
incorporated by reference in their entireties.
Claims
What is claimed is:
1. A computer-implemented method of analyzing image data to
automatically ensure consistent image capture parameters, the
method comprising, via a processor: accessing a set of digital
image data depicting an aerial view of an area, the set of digital
image data captured at a time of day and at a location; identifying
a set of image capture parameters from the set of digital image
data; accessing, based on at least one of the time of day or the
location at which the set of digital image data was captured, a set
of baseline image capture parameters corresponding to at least a
portion of the set of image capture parameters; comparing at least
the portion of the set of image capture parameters to the set of
baseline image capture parameters; based upon the comparing,
determining that the set of digital image data is not consistent
with the set of baseline image capture parameters; and in response
to the determining, generating, by the processor, a digital image
recapture instruction according to how the set of digital image
data is not consistent with the set of baseline image capture
parameters.
2. The computer-implemented method of claim 1, further comprising:
transmitting the digital image recapture instruction to a component
that captured the set of digital image data.
3. The computer-implemented method of claim 2, wherein the
component that captured the set of digital image data is configured
to execute the digital image recapture instruction.
4. The computer-implemented method of claim 2, further comprising:
receiving, from the component, an additional set of digital image
data; identifying an additional set of image capture parameters
from the additional set of digital image data; comparing the
additional set of image capture parameters to the set of baseline
image capture parameters; and based upon the comparing of the
additional set of image capture parameters, determining that the
additional set of digital image data is consistent with the set of
baseline image capture parameters.
5. The computer-implemented method of claim 1, further comprising:
transmitting the digital image recapture instruction to a component
configured to communicate with an image sensor that captured the
set of digital image data.
6. The computer-implemented method of claim 1, wherein generating
the digital image recapture instruction comprises: generating a
notification indicating how the set of digital images is not
consistent with the set of baseline image capture parameters.
7. The computer-implemented method of claim 1, wherein generating
the digital image recapture instruction comprises: determining a
set of changes needed to be consistent with the set of baseline
image capture parameters; and generating a computer-executable
instruction according to the set of changes.
8. The computer-implemented method of claim 1, wherein accessing
the set of digital image data depicting the aerial view of the area
comprises: receiving the set of digital image data from a component
that captured the set of digital image data.
9. The computer-implemented method of claim 1, wherein comparing at
least the portion of the set of image capture parameters to the set
of baseline image capture parameters comprises: for each of at
least the portion of the set of image capture parameters,
calculating a difference between the image capture parameter and
the corresponding baseline image capture parameter.
10. A system for analyzing image data to automatically ensure
consistent image capture parameters, comprising: a memory
configured to store non-transitory computer executable
instructions; and a processor interfacing with the memory, and
configured to execute the non-transitory computer executable
instructions to cause the processor to: access a set of digital
image data depicting an aerial view of an area, the set of digital
image data captured at a time of day and at a location, identify a
set of image capture parameters from the set of digital image data,
access, based on at least one of the time of day or the location at
which the set of digital image data was captured, a set of baseline
image capture parameters corresponding to at least a portion of the
set of image capture parameters, compare at least the portion of
the set of image capture parameters to the set of baseline image
capture parameters, based upon the comparing, determine that the
set of digital image data is not consistent with the set of
baseline image capture parameters, and in response to the
determining, generate a digital image recapture instruction
according to how the set of digital image data is not consistent
with the set of baseline image capture parameters.
11. The system of claim 10, further comprising: a transceiver
configured to communicate via at least one network connection;
wherein the processor is configured to execute the non-transitory
computer executable instructions to further cause the processor to:
transmit, via the transceiver, the digital image recapture
instruction to a component that captured the set of digital image
data.
12. The system of claim 11, wherein the component that captured the
set of digital image data is configured to execute the digital
image recapture instruction.
13. The system of claim 11, wherein the processor is configured to
execute the non-transitory computer executable instructions to
further cause the processor to: receive, from the component via the
transceiver, an additional set of digital image data, identify an
additional set of image capture parameters from the additional set
of digital image data, compare the additional set of image capture
parameters to the set of baseline image capture parameters, and
based upon the comparing of the additional set of image capture
parameters, determine that the additional set of digital image data
is consistent with the set of baseline image capture
parameters.
14. The system of claim 10, further comprising: a transceiver
configured to communicate via at least one network connection;
wherein the processor is configured to execute the non-transitory
computer executable instructions to further cause the processor to:
transmit, via the transceiver, the digital image recapture
instruction to a component configured to communicate with an image
sensor that captured the set of digital image data.
15. The system of claim 10, wherein to generate the digital image
recapture instruction, the processor is configured to: generate a
notification indicating how the set of digital images is not
consistent with the set of baseline image capture parameters.
16. The system of claim 10, wherein to generate the digital image
recapture instruction, the processor is configured to: determine a
set of changes needed to be consistent with the set of baseline
image capture parameters, and generate a computer-executable
instruction according to the set of changes.
17. The system of claim 10, wherein to access the set of digital
image data depicting the aerial view of the area, the processor is
configured to: receive the set of digital image data from a
component that captured the set of digital image data.
18. The system of claim 10, wherein to compare at least the portion
of the set of image capture parameters to the set of baseline image
capture parameters, the processor is configured to: for each of at
least the portion of the set of image capture parameters, calculate
a difference between the image capture parameter and the
corresponding baseline image capture parameter.
Description
TECHNICAL FIELD
The present disclosure is directed to analyzing image data to
automatically ensure consistent digital image capture parameters.
More particularly, the present disclosure is directed to systems
and methods for analyzing digital image data to determine whether
digital images were captured according to a set of parameters meant
to ensure or improve consistency.
BACKGROUND
Aerial imagery generally includes image data that is captured from
a vantage point located above an object that is depicted in the
image data. The use of aerial imagery is increasing as the amount
of devices and components used to capture aerial imagery increases.
For instance, unmanned aerial vehicles (UAVs; i.e., "drones") and
satellites are increasing in amount and usage. Generally, aerial
imagery may be used in certain applications, such as supplementing
mapping applications and creating graphical and video productions
including promotional materials and movies.
Because aerial imagery may be captured by various components and in
various conditions or circumstances, aerial imagery is often not
consistent. For example, aerial imagery captured by satellites does
not have the same level of detail as aerial imagery captured by
drones. Entities that analyze and process aerial imagery are thus
often not afforded the benefit of consistent image data, and
certain applications may be limited or ineffective. Additionally,
these entities have no way to automatically or dynamically request
the recapture of aerial imagery.
Accordingly, there is an opportunity to automatically analyze image
data to ensure or improve consistency with a set of parameters, and
facilitate certain actions to recapture image data so that the
recaptured image data is consistent with the set of parameters.
BRIEF SUMMARY
In one aspect, a computer-implemented method of analyzing image
data to automatically ensure consistent image capture parameters
may be provided. The method may include, via one or more
processors, servers, sensors, and/or transceivers: (1) accessing a
set of digital image data depicting an aerial view of an area; (2)
identifying a set of image capture parameters from the set of
digital image data; (3) accessing a set of baseline image capture
parameters corresponding to at least a portion of the set of image
capture parameters; (4) comparing at least the portion of the set
of image capture parameters to the set of baseline image capture
parameters; (5) based upon the comparing, determining that the set
of digital image data is not consistent with the set of baseline
image capture parameters; and/or (6) in response to the
determining, generating a digital image recapture instruction
according to how the set of digital image data is not consistent
with the set of baseline image capture parameters. The method may
include additional, less, or alternate actions, including those
discussed elsewhere herein.
In another aspect, a computer system for analyzing image data to
automatically ensure consistent image capture parameters may be
provided. The system may include a memory configured to store
non-transitory computer executable instructions, and a processor
interfacing with the memory, and configured to execute the
non-transitory computer executable instructions to cause the
processor to: (1) access a set of digital image data depicting an
aerial view of an area; (2) identify a set of image capture
parameters from the set of digital image data; (3) access a set of
baseline image capture parameters corresponding to at least a
portion of the set of image capture parameters; (4) compare at
least the portion of the set of image capture parameters to the set
of baseline image capture parameters; (5) based upon the comparing,
determine that the set of digital image data is not consistent with
the set of baseline image capture parameters; and/or (6) in
response to the determining, generate a digital image recapture
instruction according to how the set of digital image data is not
consistent with the set of baseline image capture parameters.
BRIEF DESCRIPTION OF THE DRAWINGS
The figures described below depict various aspects of the system
and methods disclosed herein. It should be understood that each
figure depicts an embodiment of a particular aspect of the
disclosed system and methods, and that each of the figures is
intended to accord with a possible embodiment of thereof. Further,
wherever possible, the following description refers to the
reference numerals included in the following figures, in which
features depicted in multiple figures are designated with
consistent reference numerals.
FIG. 1 depicts an overview of an exemplary computer system of
components configured to facilitate various functionalities, in
accordance with some embodiments.
FIG. 2 depicts an exemplary signal diagram associated with
analyzing image data to ensure image capture consistency, in
accordance with some embodiments.
FIGS. 3 and 4 depict exemplary interfaces indicating image capture
inconsistencies, in accordance with some embodiments.
FIG. 5 is an exemplary flow diagram associated with analyzing image
data to automatically ensure consistent image capture parameters,
in accordance with embodiments.
FIG. 6 is a block diagram of an exemplary computer server, in
accordance with some embodiments.
DETAILED DESCRIPTION
The present embodiments may relate to, inter alia, technology for
analyzing image data to automatically ensure consistent digital
image capture parameters. Aerial images are conventionally used for
various applications and processes, where certain components and
parameters of the aerial image data are varied depending on the
component that captured the aerial image data, the conditions of
the capture, and/or other factors. Because of this, the results of
the image analyses are often inconsistent. To alleviate these
shortcomings, the present embodiments analyze captured aerial image
data to effectively and efficiently assess whether the aerial image
data is consistent with a set of baseline parameters.
According to certain aspects, systems and methods may retrieve or
otherwise access a set of digital image data, where in some
embodiments the digital image data may depict an aerial view of an
area or neighborhood in which a set of properties or other
structures may be located. Although the digital image data may
primarily or solely include aerials image, such as digital images
acquired via airborne vehicles, in some embodiments, the digital
image data may alternatively include digital images acquired via
other sources, such as via cameras or video recorders mounted on
homes, smart or autonomous vehicles, or mobile devices. In other
words, the digital image data may include airborne vehicle image
data, smart or intelligent home image data, smart or autonomous
vehicle image data, and/or mobile device and/or social media image
data.
The systems and methods may analyze the set of digital image data
to identify parameters associated with the capture of the digital
image data, and may access baseline parameters that correspond to
the identified parameters. The systems and methods may compare the
identified parameters of the digital image data to the baseline
parameters to determine whether the identified parameters are
consistent with the baseline parameters (i.e., whether the digital
image data is consistent with parameters that may be considered
acceptable). If the identified parameters are not consistent, the
systems and methods may automatically facilitate the capture of
additional digital image data that may also be analyzed for
consistency.
The systems and methods therefore offer numerous benefits. In
particular, instead of analyzing different sets of digital image
data that is often inconsistent across each set, the systems and
methods ensure that each set of digital image data is consistent
with respect to a set of baseline parameters. This results in more
effective image analysis and more effective applications of the
image analysis. Additionally, the end users of the applications
(e.g., customers) are afforded the benefit of more accurate
analyses. It should be appreciated that additional benefits are
envisioned.
The systems and methods discussed herein address a challenge that
is particular to image data analysis. In particular, the challenge
relates to a difficulty in ensuring consistency across sets of
image data. This is particularly apparent in situations in which
consistent image data improves the effectiveness and efficiency of
certain applications (e.g., processing aerial image data). In
conventional situations, entities process image data sets without
accounting for inconsistencies and/or with no channel or ability to
remedy inconsistent image data. In contrast, the systems and
methods utilize network connections to effectively and efficiently
ensure image data consistency and automatically facilitate the
recapture of image data that is deemed to be inconsistent.
Therefore, because the systems and methods employ the collection,
analysis, and communication of image data, the systems and methods
are necessarily rooted in computer technology in order to overcome
the noted shortcomings that specifically arise in the realm of
image data analysis.
According to certain implementations, the systems and methods may
support a dynamic, real-time or near-real-time collection,
analysis, and communication of any applicable data. In particular,
the systems and methods may dynamically and automatically access
image data from components in real-time or near-real-time, may
automatically and dynamically analyze the image data, and may
automatically and dynamically generate and transmit notifications
or instructions resulting from the analyses in real-time or
near-real-time. In this regard, individuals are afforded the
benefit of effective and relevant image data analysis and retrieval
in real-time or near-real-time.
Exemplary System and Components Thereof
FIG. 1 illustrates an overview of a system 100 of components
configured to facilitate the systems and methods. It should be
appreciated that the system 100 is merely an example and that
alternative or additional components are envisioned.
As illustrated in FIG. 1, the system 100 may include a set of
properties 102, each of which may be any type of building,
structure, or the like. For example, the properties 102 may be any
single- or multi-unit house, flat, townhome, apartment building,
condo building, commercial building, auxiliary building for a
property (e.g., a garage), or the like. In one implementation, the
properties 102 may be void of a physical structure, and may instead
consist of an empty lot or land. FIG. 1 depicts two properties 102,
however it should be appreciated that fewer or more properties are
envisioned.
The system 100 may further include a set of aerial vehicles 103
capable of any type of air travel or flight. According to
embodiments, the aerial vehicle(s) 103 may be unmanned aerial
vehicles (UAVs; aka "drones") or may be manned by a pilot (e.g.,
airplane, helicopter, etc.). If the aerial vehicle(s) 103 is a
UAV(s), the UAV(s) may be autonomously controlled or may be
controlled remotely. Each of the set of aerial vehicles 103 may be
configured with one or more image sensors that may be capable of
capturing digital image data, where the image sensor(s) may be
controlled autonomously, or locally or remotely by an individual.
It should be appreciated that each of the set of aerial vehicles
103 may be configured with one of more image sensors, video
recorders, and/or cameras. In some embodiments, each of the set of
aerial vehicles 103 may be configured with a memory device for
storing any image data. FIG. 1 depicts two aerial vehicles 103,
however it should be appreciated that fewer or more aerial vehicles
are envisioned.
In operation, the image sensor(s) (or cameras) of the set of aerial
vehicles 103 may be configured to capture digital images that
depict various portions of the property(ies) 102. In particular,
the digital images may depict exterior portions of the
property(ies) 102, such as roofs, entryways, exterior materials,
foundations, yards, auxiliary buildings, and/or any other physical
structures or elements associated with the property(ies) 102 that
may be visible.
In addition to aerial digital images of a property 102 captured by
one or more drones or aerial vehicles 103, other digital images of
a property 102 may be acquired. For instance, digital images of the
property 102 may be acquired by one or more image sensors or
cameras of a smart or autonomous vehicle 104, a vehicle dashboard
mounted camera, a user mobile device 105, surrounding smart or
intelligent homes 102, and/or additional source(s) 106 such as, for
example, internet websites or social networking services. In
embodiments, the acquired digital images associated with a property
102 may be organized into a data set for the property 102 and
transmitted to a processor via a network(s) 110 for analysis.
Further, the system 100 may also include a processing server 115
and a set of retail terminals 112 that may be in communication via
the one or more networks 110. In certain embodiments, the
network(s) 110 may support any type of data communication via any
standard or technology (e.g., GSM, CDMA, TDMA, WCDMA, LTE, EDGE,
OFDM, GPRS, EV-DO, UWB, Internet, IEEE 802 including Ethernet,
WiMAX, Wi-Fi, Bluetooth, and others). The processing server 115 may
be configured to interface with or support a memory or storage 113
capable of storing various data. In a particular embodiment, the
memory or storage 113 may store customer account data associated
with accounts of the retail terminal(s) 112. As depicted in FIG. 1,
the processing server 115 and/or the retail terminal(s) 112 may be
configured to communicate with the set of aerial vehicles 103 via
the network(s) 110.
According to embodiments, the retail terminal(s) 112 may be
associated with an entity, business, company, enterprise,
operation, individual, or the like, that may offer or provide goods
or services for customers or clients. For example, one of the
retail terminals 112 may be associated with an internet service
provider (ISP), another of the retail terminals 112 may be
associated with a roofing service, and another of the retail
terminals 112 may be associated with an insurance provider. In
certain embodiments, the processing server 115 may be affiliated
with or unaffiliated with the retail terminal(s) 112.
In one implementation, the processing server 115 may be
incorporated into any of the retail terminal(s) 112. In another
implementation, the processing server 115 may be separate from the
retail terminal(s) 112, where the retail terminal(s) 112 may have
an existing agreement, contract, or partnership with the processing
server 115. FIG. 1 depicts two retail terminals 112, however it
should be appreciated that fewer or more retail terminals are
envisioned.
In operation, the image sensor(s) (or cameras) of the aerial
vehicle(s) 103 may capture digital image data that depicts various
portions of the property(ies) 102 and may transmit the digital
image data to the processing server 115 via the network(s) 110. The
digital image data may include a set of digital images and/or
digital videos having a set of image capture parameters associated
with how the digital image data was captured and/or with the
conditions or environment associated with the capture of the
digital image data.
After receiving the digital image data, the processing server 115
may compare the set of image capture parameters to a set of
baseline image capture parameters. Based upon the comparison, the
processing server 115 may determine whether the digital image data
is consistent with the set of baseline image capture parameters
(i.e., whether the digital image data is suitable for analysis
and/or further processing). If the processing server 115 determines
that the digital image data is consistent with the set of baseline
image capture parameters, the processing server 115 may perform
further analyses or processing of the digital image data, including
communication with the set of retail terminals 112 or other
functionality. If the processing server 115 determines that the
digital image data is not consistent with the set of baseline image
capture parameters, the processing server 115 may generate and
transmit an instruction or notification to at least one of the set
of aerial vehicles 103 to cause the at least aerial vehicle 103 to
capture additional image data that the processing server 115 may
subsequently analyze for consistency with the set of baseline image
capture parameters. These and additional functionalities are
described in further detail with respect to FIG. 2.
Exemplary Signal Diagram for Ensuring Image Consistency
FIG. 2 depicts a signal diagram 200 associated with certain
functionalities related to analyzing image data to automatically
ensure consistent image capture parameters. The signal diagram 200
may include various components including: an image source 220 (such
as one of the image sensors or cameras of the aerial vehicle(s) 103
and/or other image sensors as discussed with respect to FIG. 1) and
a processing server 215 (such as the processing server 115 as
discussed with respect to FIG. 1). Although FIG. 2 depicts the
processing server 215 as performing various of the image analyses
and other processing elements, it should be appreciated that the
functionalities may be performed by any combination of the image
source 220 and the processing server 215.
The signal diagram 200 may begin when the image source 220 captures
(230) image data. According to some embodiments, the image data may
be digital image data that consists of aerial image data of an area
in which a set of properties may be located. In one implementation,
there may be one or more of the image source 220, where the image
source(s) 220 may be associated with a manned or unmanned aerial
vehicle capable of airborne flight. Other image sources may be
used, such as home-mounted, vehicle-mounted, and/or mobile
device-mounted image sources or cameras. In one optional
implementation, the image source 220 may access image data that was
previously captured by the image source 220 itself or by another
component. The image source 220 may be configured to store the
image data, such as in a memory component.
In one optional implementation, the processing server 215 may
request (232) image data from the image source 220. According to
embodiments, the processing server 215 may automatically request
the image data periodically (e.g., once every ten seconds, once
every minute, once every hour), or a user of the processing server
215 may cause the processing server 215 to request the image data.
Additionally, the processing server 215 may request specific image
data, such as image data captured within a specified timeframe,
image data of a specific location or area, and/or image data
according to other parameters.
After the image source 220 captures or otherwise accesses the image
data, or receives a request from the processing server 215, the
image source 220 may transmit (234) or provide the image data to
the processing server 215. In certain embodiments, the image source
220 may transmit the image data via any type of network connection,
and optionally according to any request received from the
processing server 215.
After receiving the image data, the processing server 215 may
identify (236), from the image data, a set of image capture
parameters. It should be appreciated that the processing server 215
may use any type of image processing, machine learning, or computer
vision process, technique, calculation, algorithm, and/or the like
to analyze the image data. In one implementation, the processing
server 215 may be configured to analyze the image data to identify
or recognize certain objects, as well as portions or sections of
the objects, that may be depicted in the image data.
According to some embodiments, the set of image capture parameters
may be associated with how the digital image data was captured
and/or with the conditions or environment associated with the
capture of the digital image data. For example, the set of image
capture parameters may include an elevation, a distance from the
object(s) depicted in the image data, weather information (e.g.,
visibility, humidity, temperature, wind speed and direction, air
pressure), resolution, type of image capture component (e.g.,
drone, satellite, etc.), exposure, aperture, contrast, clarity,
sharpness, saturation, highlights, shadows, temperature, tint,
vignette, grain, fade, shadows, and/or the like. The set of image
capture parameters may include values or metrics for any or all of
the parameters identified herein. For example, an aerial image may
have been captured by a drone (i.e., type of image capture
component) and may have an elevation parameter of 850 m.
In one implementation, the processing server 215 may access (or the
image data may include) various sensor data that may indicate a
portion of the image capture parameters. For example, the
processing server 215 may access an altimeter reading that
indicates an elevation at which the digital image data was
captured.
The set of image capture parameters may be determined from the
image data itself, may be included in metadata associated with the
image data, may be locally stored or accessed, and/or may be
accessed from a third party source (e.g., a weather source). It
should be appreciated that the processing server 215 may identify a
portion or all of the available image capture parameters. Further,
in cases in which the image data includes multiple images, each
image may have different image capture parameters present as well
as different values or metrics for the image capture
parameters.
The processing server 215 may access (238) a set of baseline image
capture parameters. According to some embodiments, the set of
baseline image capture parameters may include values or metrics (or
ranges of values or metrics) for any or all of the parameters
identified herein (e.g., an elevation, a distance from the
object(s) depicted in the image data, weather information (e.g.,
visibility, humidity, temperature, wind speed and direction, air
pressure), resolution, type of image capture component (e.g.,
drone, satellite, etc.), exposure, aperture, contrast, clarity,
color scheme, sharpness, saturation, highlights, shadows,
temperature, tint, vignette, grain, fade, shadows, and/or the
like). For example, a distance to target parameter may specify that
an aerial image should be captured from between 80 m-200 m. For
further example, a resolution parameter may specify that an aerial
image should have a minimum resolution of 1.0 Megapixels. In
certain embodiments, the processing server 215 may access any
baseline capture parameters that match those that are included in
the set of image capture parameters.
It should be appreciated that the set of baseline image capture
parameters may vary based upon certain factors (e.g., location,
weather conditions, time of day, time of year, day of week, etc.).
For example, the acceptable elevation for image capture may be
different for images captured in Denver than it is for images
captured in New York City. For further example, the acceptable
image brightness may be different for images captured after dusk
than it is for images captured in daylight. Accordingly, the
baseline capture parameters that the processing server 215 accesses
may vary based upon one or more of these factors.
The processing server 215 may compare (240) the set of image
capture parameters included in the image data to the set of
baseline image capture parameters. In particular, the processing
server 215 may compare each of the set of image capture parameters
to the corresponding baseline image capture parameter to calculate
a difference (e.g., an absolute difference or a percentage
difference). Additionally or alternatively, the processing server
215 may determine whether each of the set of image capture
parameters meets a requirement, threshold, amount, or range of the
corresponding baseline image capture parameter. For example, if a
color scheme baseline parameter requires that an aerial image be in
color, and an aerial image is in black and white, then the color
scheme parameter of the aerial image does not meet the
corresponding baseline parameter.
The processing server 215 may determine (242) whether the set of
image capture parameters included in the image data is consistent
with the set of baseline image capture parameters. In a particular
implementation, the processing server 215 may determine whether all
of the set of image capture parameters are consistent with the
corresponding baseline image capture parameters; and if any of the
set of image capture parameters is not consistent, then the
processing server 215 may deem that the set of image capture
parameters is not consistent (and vice-versa). In another
implementation, the processing server 215 may determine whether a
certain amount or percentage of the set of image capture parameters
is consistent, and if so, then the processing server 215 may deem
that the set of image capture parameters is consistent (and
vice-versa). In a further implementation, the processing server 215
may determine whether the values or metrics of the set of image
capture parameters (or a portion thereof) is within a certain
amount or percentage of the corresponding values or metrics of the
set of baseline image capture parameters, and if so, then the
processing server 215 may deem that the set of image capture
parameters is consistent (and vice-versa). It should be appreciated
that the processing server 215 may employ additional or alternative
techniques, algorithms, calculations, or the like to determine
consistency or compliance.
If the processing server 215 determines that the set of image
capture parameters included in the image data is consistent with
the set of baseline image capture parameters ("YES"), processing
may proceed to 252. In contrast, if the processing server 215
determines that the set of image capture parameters included in the
image data is not consistent with the set of baseline image capture
parameters ("NO"), the processing server 215 may generate (244) a
notification or instruction that may indicate the inconsistency or
non-compliance. In some embodiments, the instruction may be
executable by a component (e.g., the image source 220) to cause the
component to automatically capture additional image data, and/or to
adjust certain parameters or settings to achieve consistency or
compliance.
For example, if the processing server 215 determines that the image
data was captured at too great of a distance to the target, then
the instruction may cause the image source 220 to automatically
relocate to a lesser (and compliant) distance to the target. For
further example, if the processing server 215 determines that the
image data is not of a minimum required resolution, then the
instruction may cause the image source 220 to automatically adjust
its resolution to at least meet the minimum required
resolution.
The processing server 215 may transmit or provide (246) the
notification or instruction to the image source 220. In certain
embodiments, the processing server 215 may transmit the
notification or instruction via any type of network connection. In
one implementation, the processing server 215 may transmit the
notification or instruction to a component that may control the
image source 220, such as a remote control entity. In some
embodiments in which the processing server 215 sends a
notification, the image source 220 (or a component that controls
the image source 220) may display the notification for review by an
individual. Accordingly, the individual may cause the image source
220 to make certain adjustments such that additional image data may
comply or be consistent with the set of baseline image capture
parameters.
In embodiments in which the processing server 215 sends an
instruction, the image source 220 may execute the instruction to
automatically initiate appropriate adjustments. For example, the
images source 220 executing the instruction may cause a drone
including the image source 220 to adjust to a distance of 100 m
from a target.
The image source 220 may capture (248) additional image data, such
as after optionally implementing any changes or modifications that
may be included in the notification or instruction. After the image
source 220 captures or otherwise accesses the additional image
data, the image source 220 may transmit (250) or provide the
additional image data to the processing server 215 via any type of
network connection.
At 252, the processing server 215 may process or analyze the image
data (or the additional image data). It should be appreciated that
the processing server 215 may perform any type of processing or
analysis on the image data, as well as interface with additional
components and entities (e.g., the set of retail terminals 112 as
discussed with respect to FIG. 1), to provide the additional
components and entities with certain results of the processing or
analysis. For example, the processing server 215 may determine a
set of information about a set of properties depicted in the image
data (or the additional image data), and transmit the set of
information to the set of retail terminals 112.
Exemplary Notification Interfaces
FIGS. 3 and 4 illustrate exemplary interfaces depicting
notifications resulting from digital image analyses. An electronic
device (e.g., a mobile device, such as a smartphone, smart watch,
wearable, or a computer terminal) may be configured to display the
interfaces and/or receive selections and inputs via the interfaces.
For example, a dedicated application that is configured to operate
on the electronic device may display the interfaces. The electronic
device may be associated with a component configured to capture
digital images, where a user of the electronic device may review
the information of the interfaces and facilitate appropriate
adjustments. It should be appreciated that the interfaces are
merely examples and that alternative or additional content is
envisioned.
FIG. 3 depicts an interface 300 including a notification related to
an analysis of digital image data, where the notification indicates
that the digital image data is not consistent with baseline
parameters. In particular, the interface 300 indicates that the
images were captured at an elevation of 110 m, but that the
acceptable elevation range for image capture is 80-100 m. The
interface 300 advises that the elevation of the image capture
component (here, a drone) should be adjusted to meet the acceptable
elevation range.
FIG. 4 depicts another interface 400 including a notification
related to an analysis of digital image data, where the
notification indicates that the digital image data is not
consistent with baseline parameters. In particular, the interface
400 indicates that the images were captured at a low resolution,
and that the minimum resolution is 1.0 MP. The interface 400
advises that the resolution setting of the image capture component
(here, a drone) should be adjusted to meet the minimum.
Exemplary Flow Chart for Ensuring Consistent Image Parameters
FIG. 5 depicts a block diagram of an exemplary computer-implemented
method 500 of analyzing image data to automatically ensure
consistent image capture parameters. The method 500 may be
facilitated by a processing server (such as the processing server
115) that may communicate with a set of image capture components
and various other data sources or components via one or more
network connections.
The method 500 may begin with the processing server accessing
(block 505) a set of digital image data that may depict an aerial
(or side, ground, or other) view of an area. For instance, the
digital image data may include aerial digital images or image data
acquired via one or more drones. The digital image data may or may
not also include digital images or image data acquired via one or
more home-mounted, vehicle-mounted, and/or mobile device-mounted
image sensors or cameras.
In certain embodiments, the area may include at least a portion of
a neighborhood, region, zone, and/or the like, that may be
populated by a set of properties or other physical structures. The
processing server may access the set of digital image data locally,
or may request and/or receive the set of digital image data from a
component that captured the set of digital image data, or from a
component configured to communicate with an image sensor that
captured the set of digital image data.
The processing server may identify (block 510) a set of image
capture parameters from the set of digital image data. In some
embodiments, the set of image capture parameters may include values
or metrics (or ranges of values or metrics) for any or all of the
parameters identified herein (e.g., an elevation, a distance from
the object(s) depicted in the image data, weather information
(e.g., visibility, humidity, temperature, wind speed and direction,
air pressure), resolution, type of image capture component (e.g.,
drone, satellite, etc.), exposure, aperture, contrast, clarity,
color scheme, sharpness, saturation, highlights, shadows,
temperature, tint, vignette, grain, fade, shadows, and/or the
like).
The processing server may access (block 515) a set of baseline
image capture parameters corresponding to at least a portion of the
set of image capture parameters. In some embodiments, the set of
baseline image capture parameters may have values or metrics, or
ranges of values or metrics, that may be considered acceptable, a
minimum, a maximum, or another designation. The processing server
may access those baseline parameters that correspond to the set of
image capture parameters identified in block 510 that include a
value or metric.
The processing server may compare (block 520) at least the portion
of the set of image capture parameters to the set of baseline image
capture parameters. In some embodiments, the processing server may,
for each of the at least the portion of the set of image capture
parameters, calculate a difference between the image capture
parameter and the corresponding baseline image capture
parameter.
The processing server may determine (block 525) whether the set of
digital image data is consistent with the set of baseline image
capture parameters. In embodiments, the processing server may
determine that at least a portion of the set of calculated
differences at least meets a threshold amount or percentage. It
should be appreciated that the processing server may determine
consistency according to other techniques, algorithms,
calculations, and the like.
If the processing server determines that the set of digital image
data is consistent with the set of baseline image capture
parameters ("YES"), processing may end, repeat, or proceed to other
functionality, such as performing various applications based upon
the digital image data. If the processing server determines that
the set of digital image data is not consistent with the set of
baseline image capture parameters ("NO"), the processing server may
generate (block 530) a digital image recapture instruction
according to how the set of digital image data is not consistent
with the set of baseline image capture parameters.
According to certain embodiments, the digital image recapture
instruction may be in the form of a computer-executable instruction
or a notification that may be displayable by a component (e.g., in
a user interface). In one embodiment, the digital image recapture
instruction may direct a drone or other source of aerial images or
image data to take one or more new or additional aerial pictures or
images. In one implementation, the processing server may determine
a set of changes needed to be consistent with the set of baseline
image capture parameters, and may generate the digital image
recapture instruction according to the set of changes.
The processing server may transmit (block 535) the digital image
recapture instruction to a component that captured the set of
digital image data. In some embodiments, the component may instead
be configured to communicate with an image sensor that captured the
set of digital image data. After receiving the digital image
recapture instruction, the component may execute the digital image
recapture instruction to cause any changes or adjustments to be
implemented, acquire one or more new or additional aerial or other
images or pictures, and/or may display the digital image recapture
instruction for review by an individual. After block 535,
processing may return to block 505 at which the processing server
may access an additional set of digital image data, presumably
captured according to the digital image recapture instruction. The
processing server may process the additional set of digital image
data or images accordingly.
Exemplary Hardware Diagram
FIG. 6 illustrates a diagram of an exemplary server 615 (such as
the processing server 115 as discussed with respect to FIG. 1) in
which the functionalities as discussed herein may be implemented.
It should be appreciated that the server 615 may be configured to
be connect to and communicate with various entities, components,
and devices, as discussed herein.
The server 615 may include a processor 672 as well as a memory 678.
The memory 678 may store an operating system 679 capable of
facilitating the functionalities as discussed herein as well as a
set of applications 675 (i.e., machine readable instructions). For
example, one of the set of applications 675 may be an image
analysis application 690 configured to analyze images to assess
parameter consistency, and an instruction application 691
configured to generate and transmit instructions and notifications
according to parameter consistency analyses. It should be
appreciated that one or more other applications 692 are
envisioned.
The processor 672 may interface with the memory 678 to execute the
operating system 679 and the set of applications 675. According to
some embodiments, the memory 678 may also include image data 680
that the image analysis application 690 may access and analyze. The
memory 678 may include one or more forms of volatile and/or
non-volatile, fixed and/or removable memory, such as read-only
memory (ROM), electronic programmable read-only memory (EPROM),
random access memory (RAM), erasable electronic programmable
read-only memory (EEPROM), and/or other hard drives, flash memory,
MicroSD cards, and others.
The server 615 may further include a communication module 677
configured to communicate data via one or more networks 610.
According to some embodiments, the communication module 677 may
include one or more transceivers (e.g., WWAN, WLAN, and/or WPAN
transceivers) functioning in accordance with IEEE standards, 3GPP
standards, or other standards, and configured to receive and
transmit data via one or more external ports 676. For example, the
communication module 677 may receive, via the network 610, digital
image data captured by a set of components (e.g., image sensors,
such as cameras or video recorders). For further example, the
communication module 677 may transmit notifications and
communications to various components via the network 610.
The server 615 may further include a user interface 681 configured
to present information to a user and/or receive inputs from the
user. As shown in FIG. 6, the user interface 681 may include a
display screen 682 and I/O components 683 (e.g., ports, capacitive
or resistive touch sensitive input panels, keys, buttons, lights,
LEDs, speakers, microphones). According to some embodiments, the
user may access the server 615 via the user interface 681 to review
information and/or perform other functions. In some embodiments,
the server 615 may perform the functionalities as discussed herein
as part of a "cloud" network or may otherwise communicate with
other hardware or software components within the cloud to send,
retrieve, or otherwise analyze data.
In general, a computer program product in accordance with an
embodiment may include a computer usable storage medium (e.g.,
standard random access memory (RAM), an optical disc, a universal
serial bus (USB) drive, or the like) having computer-readable
program code embodied therein, wherein the computer-readable
program code may be adapted to be executed by the processor 672
(e.g., working in connection with the operating system 679) to
facilitate the functions as described herein. In this regard, the
program code may be implemented in any desired language, and may be
implemented as machine code, assembly code, byte code,
interpretable source code or the like (e.g., via C, C++, Java,
Actionscript, Objective-C, Javascript, CSS, XML). In some
embodiments, the computer program product may be part of a cloud
network of resources.
Exemplary Computer-Implemented Method
In one aspect, a computer-implemented method of analyzing image
data to automatically ensure consistent image capture parameters
may be provided. The method may include, via one or more
processors, servers, transceivers, and/or sensors (1) accessing a
set of digital image data depicting an aerial view of an area; (2)
identifying a set of image capture parameters from the set of
digital image data; (3) accessing a set of baseline image capture
parameters corresponding to at least a portion of the set of image
capture parameters; (4) comparing at least the portion of the set
of image capture parameters to the set of baseline image capture
parameters; (5) based upon the comparing, determining that the set
of digital image data is not consistent with the set of baseline
image capture parameters; and/or (6) in response to the
determining, generating a digital image recapture instruction
according to how the set of digital image data is not consistent
with the set of baseline image capture parameters.
The method may further include transmitting the digital image
recapture instruction to a component that captured the set of
digital image data. Additionally or alternatively, the component
that captured the set of digital image data may be configured to
execute the digital image recapture instruction.
The method may further include (i) receiving, from the component,
an additional set of digital image data; (ii) identifying an
additional set of image capture parameters from the additional set
of digital image data; (iii) comparing the additional set of image
capture parameters to the set of baseline image capture parameters;
and/or (iv) based upon the comparing, determining that the
additional set of digital image data is consistent with the set of
baseline image capture parameters.
The method may further include transmitting the digital image
recapture instruction to a component configured to communicate with
an image sensor that captured the set of digital image data.
Generating the digital image recapture instruction may include
generating a notification indicating how the set of digital images
is not consistent with the set of baseline image capture
parameters.
Generating the digital image recapture instruction may include
determining a set of changes needed to be consistent with the set
of baseline image capture parameters; and generating a
computer-executable instruction according to the set of changes.
Accessing the set of digital image data depicting the aerial view
of the area may include receiving the set of digital image data
from a component that captured the set of digital image data.
Comparing at least the portion of the set of image capture
parameters to the set of baseline image capture parameters may
include, for each of at least the portion of the set of image
capture parameters, calculating a difference between the image
capture parameter and the corresponding baseline image capture
parameter.
Determining that the set of digital image data is not consistent
with the set of baseline image capture parameters may include
determining that at least a portion of the set of calculated
differences at least meets a threshold amount or percentage.
Additional Considerations
With the foregoing, an insurance customer may opt-in to a rewards,
insurance discount, or other type of program. After the insurance
customer provides their affirmative consent, an insurance provider
remote server may collect data from the customer's mobile device,
smart home controller, or other smart devices--such as with the
customer's permission or affirmative consent. The data collected
may be related to certain functionalities or profiles, and/or
insured assets before (and/or after) an insurance-related event,
including those events discussed elsewhere herein. In return, risk
averse insureds, home owners, or home or apartment occupants may
receive discounts or insurance cost savings related to home,
renters, personal articles, auto, and other types of insurance from
the insurance provider.
In one aspect, drone data, smart or interconnected home data,
autonomous or smart vehicle data, mobile device data, social media
data, and/or other data, including the types of data discussed
elsewhere herein, may be collected or received by an insurance
provider remote server, such as via direct or indirect wireless
communication or data transmission from a smart home controller,
smart or autonomous vehicle, mobile device, other customer
computing device, or customer social media content after a customer
affirmatively consents or otherwise opts-in to an insurance
discount, reward, or other program. The insurance provider may then
analyze the data received with the customer's permission to provide
benefits to the customer. As a result, risk averse customers may
receive insurance discounts or other insurance cost savings based
upon data that reflects low risk behavior and/or technology that
mitigates or prevents risk to (i) insured assets, such as homes,
personal belongings, or vehicles, and/or (ii) home or apartment
occupants.
Although the text herein sets forth a detailed description of
numerous different embodiments, it should be understood that the
legal scope of the invention is defined by the words of the claims
set forth at the end of this patent. The detailed description is to
be construed as exemplary only and does not describe every possible
embodiment, as describing every possible embodiment would be
impractical, if not impossible. One could implement numerous
alternate embodiments, using either current technology or
technology developed after the filing date of this patent, which
would still fall within the scope of the claims.
It should also be understood that, unless a term is expressly
defined in this patent using the sentence "As used herein, the term
`_____` is hereby defined to mean . . . " or a similar sentence,
there is no intent to limit the meaning of that term, either
expressly or by implication, beyond its plain or ordinary meaning,
and such term should not be interpreted to be limited in scope
based upon any statement made in any section of this patent (other
than the language of the claims). To the extent that any term
recited in the claims at the end of this disclosure is referred to
in this disclosure in a manner consistent with a single meaning,
that is done for sake of clarity only so as to not confuse the
reader, and it is not intended that such claim term be limited, by
implication or otherwise, to that single meaning. Finally, unless a
claim element is defined by reciting the word "means" and a
function without the recital of any structure, it is not intended
that the scope of any claim element be interpreted based upon the
application of 35 U.S.C. .sctn. 112(f).
Throughout this specification, plural instances may implement
components, operations, or structures described as a single
instance. Although individual operations of one or more methods are
illustrated and described as separate operations, one or more of
the individual operations may be performed concurrently, and
nothing requires that the operations be performed in the order
illustrated. Structures and functionality presented as separate
components in example configurations may be implemented as a
combined structure or component. Similarly, structures and
functionality presented as a single component may be implemented as
separate components. These and other variations, modifications,
additions, and improvements fall within the scope of the subject
matter herein.
Additionally, certain embodiments are described herein as including
logic or a number of routines, subroutines, applications, or
instructions. These may constitute either software (code embodied
on a non-transitory, tangible machine-readable medium) or hardware.
In hardware, the routines, etc., are tangible units capable of
performing certain operations and may be configured or arranged in
a certain manner. In example embodiments, one or more computer
systems (e.g., a standalone, client or server computer system) or
one or more modules of a computer system (e.g., a processor or a
group of processors) may be configured by software (e.g., an
application or application portion) as a module that operates to
perform certain operations as described herein.
In various embodiments, a module may be implemented mechanically or
electronically. Accordingly, the term "module" should be understood
to encompass a tangible entity, be that an entity that is
physically constructed, permanently configured (e.g., hardwired),
or temporarily configured (e.g., programmed) to operate in a
certain manner or to perform certain operations described herein.
Considering embodiments in which modules are temporarily configured
(e.g., programmed), each of the modules need not be configured or
instantiated at any one instance in time. For example, where the
modules comprise a general-purpose processor configured using
software, the general-purpose processor may be configured as
respective different modules at different times. Software may
accordingly configure a processor, for example, to constitute a
particular module at one instance of time and to constitute a
different module at a different instance of time.
Modules can provide information to, and receive information from,
other modules. Accordingly, the described modules may be regarded
as being communicatively coupled. Where multiple of such modules
exist contemporaneously, communications may be achieved through
signal transmission (e.g., over appropriate circuits and buses)
that connect the modules. In embodiments in which multiple modules
are configured or instantiated at different times, communications
between such modules may be achieved, for example, through the
storage and retrieval of information in memory structures to which
the multiple modules have access. For example, one module may
perform an operation and store the output of that operation in a
memory device to which it is communicatively coupled. A further
module may then, at a later time, access the memory device to
retrieve and process the stored output. Modules may also initiate
communications with input or output devices, and can operate on a
resource (e.g., a collection of information).
The various operations of example methods described herein may be
performed, at least partially, by one or more processors that are
temporarily configured (e.g., by software) or permanently
configured to perform the relevant operations. Whether temporarily
or permanently configured, such processors may constitute
processor-implemented modules that operate to perform one or more
operations or functions. The modules referred to herein may, in
some example embodiments, comprise processor-implemented
modules.
Similarly, the methods or routines described herein may be at least
partially processor-implemented. For example, at least some of the
operations of a method may be performed by one or more processors
or processor-implemented modules. The performance of certain of the
operations may be distributed among the one or more processors, not
only residing within a single machine, but deployed across a number
of machines. In some example embodiments, the processor or
processors may be located in a single location (e.g., within a home
environment, an office environment or as a server farm), while in
other embodiments the processors may be distributed across a number
of locations.
The performance of certain of the operations may be distributed
among the one or more processors, not only residing within a single
machine, but deployed across a number of machines. In some example
embodiments, the one or more processors or processor-implemented
modules may be located in a single geographic location (e.g.,
within a home environment, an office environment, or a server
farm). In other example embodiments, the one or more processors or
processor-implemented modules may be distributed across a number of
geographic locations.
Unless specifically stated otherwise, discussions herein using
words such as "processing," "computing," "calculating,"
"determining," "presenting," "displaying," or the like may refer to
actions or processes of a machine (e.g., a computer) that
manipulates or transforms data represented as physical (e.g.,
electronic, magnetic, or optical) quantities within one or more
memories (e.g., volatile memory, non-volatile memory, or a
combination thereof), registers, or other machine components that
receive, store, transmit, or display information. Some embodiments
may be described using the expression "coupled" and "connected"
along with their derivatives. For example, some embodiments may be
described using the term "coupled" to indicate that two or more
elements are in direct physical or electrical contact. The term
"coupled," however, may also mean that two or more elements are not
in direct contact with each other, but yet still co-operate or
interact with each other. The embodiments are not limited in this
context.
As used herein any reference to "one embodiment" or "an embodiment"
means that a particular element, feature, structure, or
characteristic described in connection with the embodiment may be
included in at least one embodiment. The appearances of the phrase
"in one embodiment" in various places in the specification are not
necessarily all referring to the same embodiment. In addition, use
of the "a" or "an" are employed to describe elements and components
of the embodiments herein. This is done merely for convenience and
to give a general sense of the description. This description, and
the claims that follow, should be read to include one or at least
one and the singular also includes the plural unless it is obvious
that it is meant otherwise.
As used herein, the terms "comprises," "comprising," "includes,"
"including," "has," "having" or any other variation thereof, are
intended to cover a non-exclusive inclusion. For example, a
process, method, article, or apparatus that comprises a list of
elements is not necessarily limited to only those elements but may
include other elements not expressly listed or inherent to such
process, method, article, or apparatus. Further, unless expressly
stated to the contrary, "or" refers to an inclusive or and not to
an exclusive or. For example, a condition A or B is satisfied by
any one of the following: A is true (or present) and B is false (or
not present), A is false (or not present) and B is true (or
present), and both A and B are true (or present).
This detailed description is to be construed as exemplary only and
does not describe every possible embodiment, as describing every
possible embodiment would be impractical, if not impossible. One
could implement numerous alternate embodiments, using either
current technology or technology developed after the filing date of
this application. Upon reading this disclosure, those of skill in
the art will appreciate still additional alternative structural and
functional designs for system and a method for assigning mobile
device data to a vehicle through the disclosed principles herein.
Thus, while particular embodiments and applications have been
illustrated and described, it is to be understood that the
disclosed embodiments are not limited to the precise construction
and components disclosed herein. Various modifications, changes and
variations, which will be apparent to those skilled in the art, may
be made in the arrangement, operation and details of the method and
apparatus disclosed herein without departing from the spirit and
scope defined in the appended claims.
The particular features, structures, or characteristics of any
specific embodiment may be combined in any suitable manner and in
any suitable combination with one or more other embodiments,
including the use of selected features without corresponding use of
other features. In addition, many modifications may be made to
adapt a particular application, situation or material to the
essential scope and spirit of the present invention. It is to be
understood that other variations and modifications of the
embodiments of the present invention described and illustrated
herein are possible in light of the teachings herein and are to be
considered part of the spirit and scope of the present
invention.
While the preferred embodiments of the invention have been
described, it should be understood that the invention is not so
limited and modifications may be made without departing from the
invention. The scope of the invention is defined by the appended
claims, and all devices that come within the meaning of the claims,
either literally or by equivalence, are intended to be embraced
therein. It is therefore intended that the foregoing detailed
description be regarded as illustrative rather than limiting, and
that it be understood that it is the following claims, including
all equivalents, that are intended to define the spirit and scope
of this invention.
* * * * *